Feedstock Supply Research Articles

Techno-economic and environmental assessments of storing woodchips and pellets for bioenergy applications

Storage is the critical operation within the biomass supply chain to reduce feedstock supply risks and to manage smooth year-around operations of a biorefinery or a bioenergy plant. This paper analyzed the economic and environmental impacts of four different biomass storage systems for woodchips (Outdoor-open, Outdoor-tarped, Indoor, and Silo) and two systems for pellets (Indoor and Silo). Storage cost includes the costs for handling (including ventilation in case of silo storage), infrastructure investment, and dry matter loss (DML) for each system. The estimation of total greenhouse gas (GHG) emissions includes the fugitive emissions from storage piles and emissions due to electricity and fuel consumption for each system. Among four storage systems, the outdoor-tarped ($15.0 ODMT−1, ODMT: Oven Dry Metric Ton) and silo ($5.8 ODMT−1) storage were the least-cost options for woodchips and pellets respectively. However, silo-storage could be the most promising option for storing woodchips ($5.8 ODMT−1) and pellets ($2.3 ODMT−1), if it is used for short-term (two months) and frequently (at least six times) in a year. The total GHG emissions for six-month storage were 2.8–11.8 kgCO2e ODMT−1 for woodchips and 8.6–42.0 kgCO2e ODMT−1 for pellets. During Outdoor-open storage, the lower heating value of woodchips could drop to 37% due to increased dry-matter loss (DML) and moisture content. The initial moisture content, bulk density, DML, and resource required during handling were the most sensitive parameters influenced the storage performances of both woodchips and pellets. This study has demonstrated that a combination of different storage options along the supply chain could reduce the total biomass storage cost for a biorefinery or power plant.

Blended Feedstocks for Thermochemical Conversion: Biomass Characterization and Bio-Oil Production From Switchgrass-Pine Residues Blends

An abundant, low-cost, and high-quality supply of lignocellulosic feedstock is necessary to realize the large-scale implementation of biomass conversion technologies capable of producing renewable fuels, chemicals, and products. Barriers to this goal include the variability in the chemical and physical properties of available biomass, and the seasonal and geographic availability of biomass. Blending several different types of biomass to produce consistent feedstocks offers a solution to these problems and allows for control over the specifications of the feedstocks. For thermochemical conversion processes, attributes of interest include carbon content, total ash, specific inorganics, density, particle size, and moisture content. In this work, a series of switchgrass and pine residues blends with varying physical and chemical properties were evaluated. Physical and chemical properties of the pure and blended materials were measured, including compositional analysis, elemental analysis, compressibility, flowability, density, and particle size distribution. To screen blends for thermochemical conversion behavior, the analytical technique, pyrolysis gas chromatography mass spectrometry (Py-GC/MS), was used to analyze the vapor-phase pyrolysis products of the various switchgrass/pine residues blends. The py-GC/MS findings were validated by investigating the bio-oils produced from the selected blends using a lab-scale fluidized-bed pyrolysis reactor system. Results indicate that the physical properties of blended materials are proportional to the blend ratio of pure feedstocks. In addition, pyrolysis of pine residues resulted in bio-oils with higher carbon content and lower oxygen content, while switchgrass derived pyrolysis products contained relatively greater amount of anhydrosugars and organic acids. The distribution of the pyrolysis vapors and isolated bio-oils appear to be a simple linear combination of the two feedstocks. The concentration of alkali and alkaline earth metals (Ca, K, Mg, and Na) in the blended feedstocks were confirmed to be a critical parameter due to their negative effects on the bio-oil yield. This work demonstrates that blending different sources of biomass can be an effective strategy to produce a consistent feedstock for thermochemical conversion.

A Spatial Price Determination Model for Multi‐Market Heterogeneously Distributed Resources: An Application to Forestry Markets in Sweden

The spatial dimension is a key paradigm in price determination, as attested by recent studies in the literature that highlighted the differential in market behavior between spatial and non‐spatial pricing settings. In this paper, we develop a model of spatial pricing for multi‐market heterogeneously distributed resources, with an application to the Swedish forestry sector. The focus of the model is to estimate the impact of spatial interaction on the demand for resources in terms of resource allocation, competition, and pricing. In its core, the pricing mechanism relies on a supply–demand framework. Using disaggregated data at the gridcell level for forest feedstock supply and harvesting costs in Sweden, we construct regional supply curves for each gridcell assuming a maximum transportation distance to delimit the potential market. Demand nodes are exogenously determined and are adjusted using a distance‐decay model to assess demand pressure across locations. We apply the model empirically to assess the impact on forest feedstock prices of a 20 TWh increase in biofuel production.

Biomass feedstock supply chain design – a taxonomic review and a decomposition-based methodology

In this paper, we present a taxonomic review of the literature devoted to the use of operations research approaches for the design and operation of biomass feedstock supply chains (BFSCs). A total of 185 publications that have appeared from 1989 to 2017 are classified based on (1) the embedded optimisation subproblems; (2) the modelling methodologies used for their formulations; and (3) the methods employed for their solution. Our objective of using this classification scheme is to highlight the presence of some useful substructures in a BFSC problem that can, then, be exploited in developing its solution procedure. We illustrate this idea on some generic BFSC problems and present a Dantzig–Wolfe decomposition-based methodology for developing customised approaches to effectively tackle these difficult and large-sized BFSC problems. Finally, we suggest several promising future research directions.

Managing bioethanol supply chain resiliency: a risk-sharing model to mitigate yield uncertainty risk

PurposeThe purpose of this paper is to propose a risk-sharing model to coordinate the decision-making behavior of players in a cassava-based bioethanol supply chain under random yield and demand environment, so as to mitigate the yield and demand uncertainty risk and improve the bioethanol supply chain resiliency and performance.Design/methodology/approachThe decision-making behavior under three models, namely, centralized model, decentralized model and risk-sharing model, are analyzed. An empirical test of the advantages and feasibility of the proposed risk-sharing model, as well as the test of yield uncertainty risk, risk-sharing coefficients and randomly fluctuating cassava market price on the decision-making behavior and performances are provided.FindingsThough the proposed risk-sharing model cannot achieve the supply chain performance in the centralized model, it does help to encourage the farmers and the company to increase the supply of cassava and achieve the Pareto improvement of both players compared to the decentralized model. In particular, these improvements will be enlarged as the yield uncertainty risk is higher.Practical implicationsThe findings will help decision makers in the bioethanol supply chain to understand how to mitigate the yield uncertainty risk and improve the supply chain resiliency under yield and demand uncertainty environment. It will also be conducive to ensure the supply of feedstock and the development of the bioethanol industry.Originality/valueThe proposed risk-sharing model incorporates the yield uncertainty risk, the random market demand and the hierarchical decision-making behavior structure of the bioethanol supply chain in the model.

Diverse lignocellulosic feedstocks can achieve high field‐scale ethanol yields while providing flexibility for the biorefinery and landscape‐level environmental benefits

AbstractIncreasing the diversity of lignocellulosic feedstocks accepted by a regional biorefinery has the potential to improve the environmental footprint of the facility; harvest, storage, and transportation logistics; and biorefinery economics. However, feedstocks can vary widely in terms of their biomass yields and quality characteristics (chemical composition, moisture content, etc.). To investigate how the diversity of potential biofuel cropping systems and feedstock supply might affect process and field‐scale ethanol yields, we processed and experimentally quantified ethanol production from five different herbaceous feedstocks: two annuals (corn stover and energy sorghum) and three perennials (switchgrass, miscanthus, and mixed prairie). The feedstocks were pretreated using ammonia fiber expansion (AFEX), hydrolyzed at high solid loading (~17%–20% solids, depending on the feedstock), and fermented separately using microbes engineered to utilize xylose: yeast (Saccharomyces cerevisiaeY128) or bacteria (Zymomonas mobilis8b). The field‐scale ethanol yield from each feedstock was dependent on biomass quality and cropping system productivity; however, biomass yield had a greater influence on the ethanol yield for low‐productivity crops, while biomass quality was the main driver for ethanol yields from high‐yielding crops. The process ethanol yield showed similar variability across years and feedstocks. A low process yield for corn stover was determined to result from inhibition of xylose utilization by unusually elevated levels of hydroxycinnamates (p‐coumaric and ferulic acids) in the untreated biomass and their acid and amide derivatives in the resulting hydrolyzate. This finding highlights the need to better understand factors that influence process ethanol yield and biomass quality. Ultimately we provide evidence that most feedstocks fall within a similar range of process ethanol yield, particularly for the more resistant strain Z. mobilis8b. This supports the claim that the refinery can successfully diversify its feedstock supply, enabling many social and environmental benefits that can accrue due to landscape diversification.

Supplier selection and operation planning in biomass supply chains with supply uncertainty

Bioenergy is considered a potential solution to reduce carbon footprint and fight against global warming. However, uncertainty in the harvest of biomass could lead to the instability of feedstock supply that has a significant impact on the sustainability of biomass supply chain. In this paper, we present a two-stage stochastic programming model dealing with supplier selection to stabilize feedstock supply of a biomass supply chain in uncertain environments. The model involves the first stage decisions for the supplier selection and the second-stage decisions for planning transportation, inventory and production operations. To reduce the computational burden for large instances, we propose an enhanced and regularized L-shaped decomposition algorithm to solve the model. The applicability of this model and the performance of the solution method are evaluated by numerical studies. Sensitivity analysis shows that the values of some parameters related to suppliers have significant impacts on the optimal expected cost and supplier selection.

Technoeconomic Analysis of Alternative Pathways of Isopropanol Production

Isopropanol is a widely used solvent and chemical. The growing demand for isopropanol, the declining supply of typical feedstocks for manufacturing isopropanol, and the increasing prices necessitat...

Energy use, greenhouse gases emission and cost effectiveness of an integrated high– and low–temperature Fisher–Tropsch synthesis plant from a lifecycle viewpoint

The lifecycle assessment of energy–greenhouse gases emission–economic performance for single low–temperature Fischer–Tropsch synthesis (LTFTS), high–temperature Fischer–Tropsch synthesis (HTFTS) and HTFTS–LTFTS co-production from coal are investigated and compared to the oil refining process. This covers feedstock supply chain and oil production at the oil refinery and Fischer–Tropsch synthesis (FTS) plants. Results show that the energy input and CO2 emission are mostly from coal mining and washing and oil production at the plant for FTS plants or oil refinery. Cost input is largely from feedstock cost and capital cost for FTS plants, crude oil cost, and transport cost for oil refining process. Compared to oil refinery pathway, FTS to oil currently presents no advantages in the aspect of lifecycle of energy use and greenhouse gases emission. However, the HTFTS-LTFTS demonstrates a favorable economic feasibility especially at a low oil price, indicating that the combined system presents high flexibility and strong market adaptability compared to traditional stand–alone HTFTS, LTFTS and oil refinery plant. Furthermore, in comparison with single HTFTS and LTFTS plants, HTFTS–LTFTS makes a big progress in CO2 emission per unit profit due to its excellent economic benefits. Such an alternative way of coal to oil has an enormous potential to simultaneously satisfy requirements of oil safety and standard of CO2 emission reduction in China.

Global energy sector emission reductions and bioenergy use: overview of the bioenergy demand phase of the EMF-33 model comparison

We present an overview of results from 11 integrated assessment models (IAMs) that participated in the 33rd study of the Stanford Energy Modeling Forum (EMF-33) on the viability of large-scale deployment of bioenergy for achieving long-run climate goals. The study explores future bioenergy use across models under harmonized scenarios for future climate policies, availability of bioenergy technologies, and constraints on biomass supply. This paper provides a more transparent description of IAMs that span a broad range of assumptions regarding model structures, energy sectors, and bioenergy conversion chains. Without emission constraints, we find vastly different CO2 emission and bioenergy deployment patterns across models due to differences in competition with fossil fuels, the possibility to produce large-scale bio-liquids, and the flexibility of energy systems. Imposing increasingly stringent carbon budgets mostly increases bioenergy use. A diverse set of available bioenergy technology portfolios provides flexibility to allocate bioenergy to supply different final energy as well as remove carbon dioxide from the atmosphere by combining bioenergy with carbon capture and sequestration (BECCS). Sector and regional bioenergy allocation varies dramatically across models mainly due to bioenergy technology availability and costs, final energy patterns, and availability of alternative decarbonization options. Although much bioenergy is used in combination with CCS, BECCS is not necessarily the driver of bioenergy use. We find that the flexibility to use biomass feedstocks in different energy sub-sectors makes large-scale bioenergy deployment a robust strategy in mitigation scenarios that is surprisingly insensitive with respect to reduced technology availability. However, the achievability of stringent carbon budgets and associated carbon prices is sensitive. Constraints on biomass feedstock supply increase the carbon price less significantly than excluding BECCS because carbon removals are still realized and valued. Incremental sensitivity tests find that delayed readiness of bioenergy technologies until 2050 is more important than potentially higher investment costs.

Protein molecular structure in relation to predicted biodegradation and nutrient supply of feedstocks and co-products from bio-oil processing with CNCPS system: Comparison Crusher Plants within Canada and within China as well as between Canada and China

Recently, rapid non-invasive advanced vibrational molecular spectroscopy has been developed to detect tissue inherent molecular structure. However, this advanced technique is seldom known by animal scientists and seldom used to study feed molecular structure in relation to nutrient utilization and availability in animals. The objectives of this study were to 1) detect the interactive association between the processing-induced protein molecular structure changes and biodegradation and intestinal digestion in ruminants using advanced vibrational molecular spectroscopy, and 2) develop a model to predict protein and carbohydrate degradation and digestions based on feed inherent protein molecular structure. The feed used for this study were various sources of feedstock (oil seeds) and co-products (canola meal, canola pellets) from ten different crushing plants in Canada and China with multi-source samples from each crushing plant. The predictable protein and carbohydrate degradable sub-fractions and nutrient supply of sub-fractions to dairy cows were evaluated with the updated Cornell Net Carbohydrate and Protein System (CNCPS 6.5). The protein molecular structure was revealed using advanced vibrational molecular spectroscopy (FT/IR-ATR). The molecular structure spectral analyses were carried out using uni- and multi-variate molecular spectral analyses. The model variable selection was carried out using SAS with a Stepwise option. The results showed that protein molecular structure spectral characteristics could be used to predict CNCPS protein and carbohydrate nutrient supply to dairy cows. Strong positive correlation was found in canola meal between rumen degraded PA2 and amide I area (r = 0.67, P < 0.001), amide I height (r = 0.73, P < 0.001), and α-helix height (r = 0.83, P < 0.001). RDPB2 was negatively correlated with α-helix height (r = −0.69, P < 0.001). Moreover, TRDC was negatively correlated with amide I area (r=-0.64, P < 0.001), amide I height (r = −0.65, P < 0.001), and α-helix height (r = −0.62, P < 0.001). It was concluded that protein and carbohydrate degradable and undegradable sub-fractions had interactive associations with the processing-induced protein molecular structure changes in co-products from bio-oil processing.

Life cycle assessment of combined bioheat and biopower production: An eco-design approach

Life cycle assessment (LCA) can be conducted in coordination with a process simulation and used as an eco-design (green design) tool by quantifying the relations between eco-design parameters and environmental impact categories. The purpose of this article is to minimize environmental life cycle impacts of combined bioheat and biopower (CBHBP) production at its design stage, and thereby ensure sustainable CBHBP production. In this study, the aim is to conduct an LCA study in coordination with a process simulation and introduce an eco-design approach to determine the environmental sustainability of a combustion-based in situ CBHBP plant based on a simulated case study. Eco-design approach in this study enabled to quantify the effect of changes in feedstock moisture content, excess air ratio, and furnace temperature on the selected LCA results (based on the contribution analysis performed) for the simulated CBHBP case study. Feedstock supply chain is the stage most affected by increases in moisture content due to the consequent higher transportation requirements. For example, increasing moisture content from 30% to 50% causes about an 18% increase in global warming (GW). Excess air ratio and furnace temperature affected the importance of CBHBP plant operation mostly due to nitrogen oxides (NOx) emission increases. As an example, the higher increases in eutrophication (ETR) (∼56%) and acidification (ACD) (∼17%) are observed between the excess air ratios of 1.2 and 1.5. In addition, with increasing furnace temperature, high increases occur in mainly ETR and then ACD. For instance, an increase from 900 to 1000○C increases ETR ∼78%; an increase from 1100 to 1200○C increases ACD ∼38%. The methodology proposed here can be applied to any system for a better environmental performance. The study ultimately incorporates a biorefinery concept intended to advance the building of a bio-based (low carbon) economy.

Life cycle assessment of wheat straw lignocellulosic bio-ethanol fuel in a local biorefinery prospective

Abstract A ″cradle-to-wheel life cycle analysis was carried out to investigate the environmental profile of bioethanol (EtOH) production from lignocellulosic wheat straw (WS) and its use as transport fuel in E10 (10% of EtOH and 90% of gasoline) and E85 (85% of EtOH and 15% of gasoline) vehicles. The aims of this study were: (i) to evaluate the environmental performance of the whole WS-EtOH supply chain and (ii) to identify the best performing feedstock for a prospective bio-refinery network in Campania Region (Southern Italy). A comparison of WS-EtOH system against the fossil counterpart (gasoline passenger car) and similar bio-based production-use chains was conducted to fulfil one of the main goals of EnerBiochem and BioPoliS projects: investigating the environmental profitability of a bio-refinery system in Campania Region. Starting from the use of residual feedstock (wheat straw) or the revaluation of marginal lands (cultivation of dedicated perennial giant reed or annul fiber sorghum), through the investigation of an advanced lignocellulosic conversion processes, this work assesses the environmental feasibility of bio-energy production in Campania Region. The WS-E10 environmental profile was driven by the gasoline input in the blend, whilst the WS-E85 results showed the relevance of the crop phase. The comparison of the different blends and the gasoline-fuelled car highlighted for E10-blends similar profiles for almost all the impact categories, nearly overlapping with the conventional vehicle. Differently, for E85 vehicles, the differences between the bio-based systems appeared amplified according to the specific impacts of the feedstock supply and the conversion steps. On the whole, Fiber Sorghum-E85 system showed the worst environmental profile whilst WS-E85 entailed the best performance.

Life cycle energy-economic-CO2 emissions evaluation of biomass/coal, with and without CO2 capture and storage, in a pulverized fuel combustion power plant in the United Kingdom

Biomass to power generation is an alternative for fossil fuel to power pathways and plays a significant role in electricity supply and CO2 emissions reduction of the United Kingdom (UK). Additionally, the UK government plans to phase out coal to power in the near future (2025), implying that all coal power plants in the future must be deployed with CO2 capture and storage (CCS). In this study, life cycle evaluation of energy use, CO2 emissions and cost requirements for pulverized fuel combustion power plants using white wood pellets and bituminous coal, a typical coal widely consumed in coal power station in the UK, as feedstocks, with and without (w/o) post-combustion CCS are investigated for deep understanding application and challenges of these technologies. The life cycle evaluation covers the whole power generation process including wood pellets/coal supply chain and electricity generation at the power plant. The analysis demonstrates that biomass or biomass/coal co-fired plants w/o CCS has no advantage in comparison to coal fired plant w/o CCS regarding the energy use due to the high energy consumption during the biomass supply chain process. From a life cycle viewpoint, CO2 released when combusting biomass will be consumed during plant growth, resulting in an approximate carbon neutral combustion process with additional CO2 emissions from the supply chain process. The biggest handicap for biomass power plants is the high operational cost of the feedstock supply chain process, with the additional high capital cost of the carbon capture plant, if considered. These results are a comprehensive guide which can help decision makers perform suitable measures to push forward development and application of coal/biomass power generation with CCS.

Sustainability impacts of increased forest biomass feedstock supply – a comparative assessment of technological solutions

ABSTRACT Sustainably managed forests provide renewable raw material that can be used for primary/secondary conversion products and as biomass for energy generation. The potentially available amounts of timber, which are still lower than annual increments, have been published earlier. Access to this timber can be challenging for small-dimensioned assortments; however, technologically improved value chains can make them accessible while fulfilling economic and environment criteria. This paper evaluates the economic, environmental and social sustainability impacts of making the potentially available timber available with current and technologically improved value chains. This paper focuses on increasing the biomass feedstock supply for energy generation. Quantified impact assessments show which improvements – in terms of costs, employment, fuel and energy use, and reduced greenhouse gas emissions – can be expected if better mechanized machines are provided. Using three different methods – Sustainability Impacts Assessment (SIA), Life Cycle Assessment (LCA), and Emission Saving Criteria (ESC) – we calculated current and innovative machine solutions in terms of fuel use, energy use, and greenhouse gas emissions, to quantify the impact of the technology choice and also the effect of the choice of assessment method. Absolute stand-alone values can be misleading in analyses, and the use of different impact calculation approaches in parallel is clarifying the limits of using LCA-based approaches. The ESC has been discussed for the recast of the Renewable Energy Directive. Potential EU-wide results are presented.

English

The oil and raffia palm species are indigenous to West and Central Africa, and their exploitation both at industrial and artisanal scale generate important quantities of renewable fibrous biomass that can be converted to high and low value bio-based products. Fibre samples were prepared from three raffia palm species drawn from three locations and Oil Palm Empty Fruit Bunch (OPEFB) from an industrial palm oil mill, all in the South West Region of Cameroon. The samples were tested for chemical composition using wet chemical methods and an elemental analyzer. The functional groups were determined by Fourier Transform Infrared Spectrometer (FT-IR) spectroscopy while morphological analysis and crystallinity were evaluated by scanning electron microscopy and powder X-ray diffraction respectively. The results obtained show that extractives-free raffia palm fibres are similar to OPEFB with respect to lignin, hemicellulose and cellulose contents, morphology, occurrence of silica bodies on the surface of fibres and internal porosity. Scanning Electron Microscopy (SEM) indicated that the diameter of raffia fibre were larger than those of OPEFB stalk and spikelet fibres. The content of extractives determined by gravimetric method showed significantly lower values for raffia biomass compared to EFB fibres. The response of the fibres to hypochlorite treatment as revealed by FT-IR and morphological studies was very similar. The raffia fibres reflected significantly lower ash content and the powder X-ray studies showed slight differences in crystallinity index between raffia and OPEFB. The variability in key characteristics of biomass from the different species of palm are within the limits of the variability shown by biomass from the same species of plants. This leads to the conclusion that, the two types of palm which are both indigenous to the West and Central Africa can serve as source of blended renewable biomass. Promotion of cultivation and conservation of existing raffia plantations presents as a strategy for a more sustainable supply of biomass feedstock for bio-based products. Key words: Raffia palm, oil palm, fiber sample, Fourier Transform Infrared Spectrometer (FT-IR), Scanning Electron Microscopy (SEM).

Using remote sensing to estimate forage biomass and nutrient contents at different growth stages

Lignocellulosic biomass is an important feedstock for the second generation bioenergy production. A sustainable supply of biomass feedstock having consistent composition is critical for a biorefinery. This requires a timely monitoring and estimation of the biomass yield and composition in the field. It is not clear if one can use the near infrared (NIR) vegetation canopy reflectance measured in the field and build a calibrate model to estimate biomass yield and nutrient contents (compositions) for the vegetation from vegetative growth through dormancy stages. In this study, the NIR canopy reflectance of a grass/legume mixture was measured in a field with a spectroradiometer with wavelength ranging from 400-2500 nm. The plants were then clipped, dried, and ground to measure the biomass yield, neutral detergent fiber (NDF), acid detergent fiber (ADF), and crude protein (CP). The measurements were conducted at the boot, peak growth, and at dormancy stages. Partial least significant regression (PLSR) models were built using data from each individual growth stage as well as all stages combined. Except for the yield model at peak growth stage and the NDF and ADF models at dormancy stage, models developed from each of the individual stages generally estimated the yield, CP, NDF, and ADF poorly, with R2CV ranging between -0.31 and 0.42. When data from all three growth stages were included, the accuracy of all models was greatly improved, with R2CV ranging between 0.77 and 0.80. Furthermore, multiple linear regression (MLR) models developed with 7–9 most significant wavelengths selected from 400-2500 nm estimated the yield, ADF, NDF, and CP equally well compared with the PLSR models. The estimates from MLR model showed strong correlations between the measured and estimated values, with R2 of 0.72, 0.67, 0.78, and 0.66 for the yield, ADF, NDF, and CP, respectively. These results indicate that biomass feedstock yield and composition can be estimated by the in-situ NIR canopy reflectance using a multiple linear regression model with 7–9 wavelengths. Further calibration is needed to use the model to other geological locations.

New Geospatial Approaches for Efficiently Mapping Forest Biomass Logistics at High Resolution over Large Areas

Adequate biomass feedstock supply is an important factor in evaluating the financial feasibility of alternative site locations for bioenergy facilities and for maintaining profitability once a facility is built. We used newly developed spatial analysis and logistics software to model the variables influencing feedstock supply and to estimate and map two components of the supply chain for a bioenergy facility: (1) the total biomass stocks available within an economically efficient transportation distance; (2) the cost of logistics to move the required stocks from the forest to the facility. Both biomass stocks and flows have important spatiotemporal dynamics that affect procurement costs and project viability. Though seemingly straightforward, these two components can be difficult to quantify and map accurately in a useful and spatially explicit manner. For an 8 million hectare study area, we used raster-based methods and tools to quantify and visualize these supply metrics at 10 m2 spatial resolution. The methodology and software leverage a novel raster-based least-cost path modeling algorithm that quantifies off-road and on-road transportation and other logistics costs. The results of the case study highlight the efficiency, flexibility, fine resolution, and spatial complexity of model outputs developed for facility siting and procurement planning.

Bioethanol Potential of Energy Sorghum Grown on Marginal and Arable Lands.

Field experiments were conducted in marginal lands, i.e., sub-humid climate and saline-land (SHS) and semi-arid climate and wasteland (SAW), to evaluate ethanol potential based on the biomass yield and chemical composition of biomass type (var. GN-2, GN-4, and GN-10) and sweet type (var. GT-3 and GT-7) hybrids of energy sorghum [Sorghum bicolor (L.) Moench] in comparison with sub-humid climate and cropland (SHC) in northern China. Results showed that environment significantly (p < 0.05) influenced plant growth, biomass yield and components, and subsequently the ethanol potential of energy sorghum. Biomass and theoretical ethanol yield of the crop grown at SHS (12.2 t ha−1 and 3,425 L ha−1, respectively) and SAW (8.6 t ha−1 and 2,091 L ha−1, respectively) were both statistically (p < 0.001) lower than values at the SHC site (32.6 t ha−1 and 11,853 L ha−1, respectively). Higher desirable contents of soluble sugar, cellulose, and hemicellulose were observed at SHS and SHC sites, while sorghum grown at SAW possessed higher lignin and ash contents. Biomass type sorghum was superior to sweet type as non-food ethanol feedstock. In particular, biomass type hybrid GN-10 achieved the highest biomass (17.4 t ha−1) and theoretical ethanol yields (5,423 L ha−1) after averaging data for all environmental sites. The most productive hybrid, biomass type GN-4, exhibited biomass and theoretical ethanol yields >42.1 t ha−1 and 14,913 L ha−1, respectively, at the cropland SHC site. In conclusion, energy sorghum grown on marginal lands showed a very lower ethanol potential, indicating a considerable lower possibility for being used as commercial feedstock supply when compared with that grown on regular croplands. Moreover, screening suitable varieties may improve energy sorghum growth and chemical properties for ethanol production on marginal lands.

Compatibility of High-Moisture Storage for Biochemical Conversion of Corn Stover: Storage Performance at Laboratory and Field Scales.

Wet anaerobic storage of corn stover can provide a year-round supply of feedstock to biorefineries meanwhile serving an active management approach to reduce the risks associated with fire loss and microbial degradation. Wet logistics systems employ particle size reduction early in the supply chain through field-chopping which removes the dependency on drying corn stover prior to baling, expands the harvest window, and diminishes the biorefinery size reduction requirements. Over two harvest years, in-field forage chopping was capable of reducing over 60% of the corn stover to a particle size of 6 mm or less. Aerobic and anaerobic storage methods were evaluated for wet corn stover in 100 L laboratory reactors. Of the methods evaluated, traditional ensiling resulted in <6% total solid dry matter loss (DML), about five times less than the aerobic storage process and slightly less than half that of the anaerobic modified-Ritter pile method. To further demonstrate the effectiveness of the anaerobic storage, a field demonstration was completed with 272 dry tonnes of corn stover; DML averaged <5% after 6 months. Assessment of sugar release as a result of dilute acid or dilute alkaline pretreatment and subsequent enzymatic hydrolysis suggested that when anaerobic conditions were maintained in storage, sugar release was either similar to or greater than as-harvested material depending on the pretreatment chemistry used. This study demonstrates that wet logistics systems offer practical benefits for commercial corn stover supply, including particle size reduction during harvest, stability in storage, and compatibility with biochemical conversion of carbohydrates for biofuel production. Evaluation of the operational efficiencies and costs is suggested to quantify the potential benefits of a fully-wet biomass supply system to a commercial biorefinery.